Distributed Extended Object Tracking Filter Through Embedded ADMM Technique

This work is concerned with the distributed extended object tracking system over a realistic network, where all nodes are required to achieve consensus on both the extent and kinematics. To this end, we first exploit an aligned velocity model to establish a tight relation between the orientation and velocity vector. Then, we use the moment-matching method to give two separate models to match the information filter (IF) framework. Later, we resort to the two models to propose a centralized IF and extend it to the distributed scenario based on the embedded alternating direction method of multipliers (ADMM) technique. To keep an agreement between nodes, an optimization function is given, followed by a consensus-based constraint. Numerical simulation together with theoretical analysis verifies the convergence and consensus of the proposed filter.